{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import QUANTAXIS as QA\n",
    "import sys\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "Account=QA.QA_Account(allow_sellopen=True,allow_t0=True,account_cookie='future_test',market_type=QA.MARKET_TYPE.FUTURE_CN)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "Broker=QA.QA_BacktestBroker()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "前期货数据暂未存储,直接获取来回测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "rb_ds=QA.QA_fetch_future_day_adv('RBL8','2017-01-01','2018-08-28')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "< QA_DataStruct_Future_day with 1 securities >"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rb_ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'future_cn'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Account.market_type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "def MACD_JCSC(dataframe,SHORT=12,LONG=26,M=9):\n",
    "    \"\"\"\n",
    "    1.DIF向上突破DEA，买入信号参考。\n",
    "    2.DIF向下跌破DEA，卖出信号参考。\n",
    "    \"\"\"\n",
    "    CLOSE=dataframe.close\n",
    "    DIFF =QA.EMA(CLOSE,SHORT) - QA.EMA(CLOSE,LONG)\n",
    "    DEA = QA.EMA(DIFF,M)\n",
    "    MACD =2*(DIFF-DEA)\n",
    "\n",
    "    CROSS_JC=QA.CROSS(DIFF,DEA)\n",
    "    CROSS_SC=QA.CROSS(DEA,DIFF)\n",
    "    ZERO=0\n",
    "    return pd.DataFrame({'DIFF':DIFF,'DEA':DEA,'MACD':MACD,'CROSS_JC':CROSS_JC,'CROSS_SC':CROSS_SC,'ZERO':ZERO})\n",
    "\n",
    "ind=rb_ds.add_func(MACD_JCSC)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "< QA_Order realorder_id Order_RIOlwfW9 datetime:2017-03-16 00:00:00 code:RBL8 amount:300 price:0 towards:2 btype:future_cn order_id:Order_RIOlwfW9 account:future_test status:queued >\n",
      "< QA_DataStruct_Future_day with 1 securities >\n",
      "receive deal\n",
      "1000000\n",
      "NOT ENOUGH MONEY FOR Order_RIOlwfW9\n",
      "< QA_Order realorder_id Order_N7kgLDdi datetime:2017-04-24 00:00:00 code:RBL8 amount:300 price:0 towards:2 btype:future_cn order_id:Order_N7kgLDdi account:future_test status:queued >\n",
      "< QA_DataStruct_Future_day with 1 securities >\n",
      "receive deal\n",
      "receive deal\n",
      "< QA_Order realorder_id Order_To0LnZ6R datetime:2017-06-16 00:00:00 code:RBL8 amount:300 price:0 towards:2 btype:future_cn order_id:Order_To0LnZ6R account:future_test status:queued >\n",
      "< QA_DataStruct_Future_day with 1 securities >\n",
      "receive deal\n",
      "receive deal\n",
      "< QA_Order realorder_id Order_B5y7xKVo datetime:2017-08-02 00:00:00 code:RBL8 amount:300 price:0 towards:2 btype:future_cn order_id:Order_B5y7xKVo account:future_test status:queued >\n",
      "< QA_DataStruct_Future_day with 1 securities >\n",
      "receive deal\n",
      "receive deal\n",
      "< QA_Order realorder_id Order_oYL3dnRj datetime:2017-09-04 00:00:00 code:RBL8 amount:300 price:0 towards:2 btype:future_cn order_id:Order_oYL3dnRj account:future_test status:queued >\n",
      "< QA_DataStruct_Future_day with 1 securities >\n",
      "receive deal\n",
      "1199038.4125\n",
      "NOT ENOUGH MONEY FOR Order_oYL3dnRj\n",
      "< QA_Order realorder_id Order_zd4AiEsW datetime:2017-10-13 00:00:00 code:RBL8 amount:300 price:0 towards:2 btype:future_cn order_id:Order_zd4AiEsW account:future_test status:queued >\n",
      "< QA_DataStruct_Future_day with 1 securities >\n",
      "receive deal\n",
      "receive deal\n",
      "< QA_Order realorder_id Order_4FNMg93m datetime:2017-11-06 00:00:00 code:RBL8 amount:300 price:0 towards:2 btype:future_cn order_id:Order_4FNMg93m account:future_test status:queued >\n",
      "< QA_DataStruct_Future_day with 1 securities >\n",
      "receive deal\n",
      "receive deal\n",
      "< QA_Order realorder_id Order_zsXxkHy6 datetime:2018-01-11 00:00:00 code:RBL8 amount:300 price:0 towards:2 btype:future_cn order_id:Order_zsXxkHy6 account:future_test status:queued >\n",
      "< QA_DataStruct_Future_day with 1 securities >\n",
      "receive deal\n",
      "receive deal\n",
      "< QA_Order realorder_id Order_pqLsA2DI datetime:2018-01-18 00:00:00 code:RBL8 amount:300 price:0 towards:2 btype:future_cn order_id:Order_pqLsA2DI account:future_test status:queued >\n",
      "< QA_DataStruct_Future_day with 1 securities >\n",
      "receive deal\n",
      "receive deal\n",
      "< QA_Order realorder_id Order_iPLGhVCX datetime:2018-02-26 00:00:00 code:RBL8 amount:300 price:0 towards:2 btype:future_cn order_id:Order_iPLGhVCX account:future_test status:queued >\n",
      "< QA_DataStruct_Future_day with 1 securities >\n",
      "receive deal\n",
      "1206798.7000000002\n",
      "NOT ENOUGH MONEY FOR Order_iPLGhVCX\n",
      "< QA_Order realorder_id Order_sG3do70w datetime:2018-04-10 00:00:00 code:RBL8 amount:300 price:0 towards:2 btype:future_cn order_id:Order_sG3do70w account:future_test status:queued >\n",
      "< QA_DataStruct_Future_day with 1 securities >\n",
      "receive deal\n",
      "receive deal\n",
      "< QA_Order realorder_id Order_dcGMh8tv datetime:2018-05-31 00:00:00 code:RBL8 amount:300 price:0 towards:2 btype:future_cn order_id:Order_dcGMh8tv account:future_test status:queued >\n",
      "< QA_DataStruct_Future_day with 1 securities >\n",
      "receive deal\n",
      "receive deal\n",
      "< QA_Order realorder_id Order_09bcEx2w datetime:2018-07-10 00:00:00 code:RBL8 amount:300 price:0 towards:2 btype:future_cn order_id:Order_09bcEx2w account:future_test status:queued >\n",
      "< QA_DataStruct_Future_day with 1 securities >\n",
      "receive deal\n",
      "receive deal\n"
     ]
    }
   ],
   "source": [
    "\n",
    "for items in rb_ds.panel_gen:\n",
    "    \n",
    "    for item in items.security_gen:\n",
    "        daily_ind=ind.loc[item.index]\n",
    "        if daily_ind.CROSS_JC.iloc[0]>0:\n",
    "            order=Account.send_order(\n",
    "                code=item.code[0], \n",
    "                time=item.date[0], \n",
    "                amount=300, \n",
    "                towards=QA.ORDER_DIRECTION.BUY_OPEN, \n",
    "                price=0, \n",
    "                order_model=QA.ORDER_MODEL.CLOSE, \n",
    "                amount_model=QA.AMOUNT_MODEL.BY_AMOUNT\n",
    "                )\n",
    "\n",
    "            if order:\n",
    "                print(order)\n",
    "                print(item)\n",
    "                Broker.receive_order(QA.QA_Event(order=order,market_data=item))\n",
    "\n",
    "\n",
    "                trade_mes=Broker.query_orders(Account.account_cookie,'filled')\n",
    "                res=trade_mes.loc[order.account_cookie,order.realorder_id]\n",
    "                order.trade(res.trade_id,res.trade_price,res.trade_amount,res.trade_time)\n",
    "        elif daily_ind.CROSS_SC.iloc[0]>0:\n",
    "            if Account.sell_available.get(item.code[0], 0)>0:\n",
    "                order=Account.send_order(\n",
    "                    code=item.code[0], \n",
    "                    time=item.date[0], \n",
    "                    amount=Account.sell_available.get(item.code[0], 0), \n",
    "                    towards=QA.ORDER_DIRECTION.SELL_CLOSE, \n",
    "                    price=0, \n",
    "                    order_model=QA.ORDER_MODEL.MARKET, \n",
    "                    amount_model=QA.AMOUNT_MODEL.BY_AMOUNT\n",
    "                    )\n",
    "                if order:\n",
    "                    Broker.receive_order(QA.QA_Event(order=order,market_data=item))\n",
    "\n",
    "\n",
    "                    trade_mes=Broker.query_orders(Account.account_cookie,'filled')\n",
    "                    res=trade_mes.loc[order.account_cookie,order.realorder_id]\n",
    "                    order.trade(res.trade_id,res.trade_price,res.trade_amount,res.trade_time)\n",
    "    Account.settle()\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>datetime</th>\n",
       "      <th>code</th>\n",
       "      <th>price</th>\n",
       "      <th>amount</th>\n",
       "      <th>cash</th>\n",
       "      <th>order_id</th>\n",
       "      <th>realorder_id</th>\n",
       "      <th>trade_id</th>\n",
       "      <th>account_cookie</th>\n",
       "      <th>commission</th>\n",
       "      <th>tax</th>\n",
       "      <th>message</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-04-24 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>2927.0</td>\n",
       "      <td>300</td>\n",
       "      <td>1.216805e+05</td>\n",
       "      <td>Order_N7kgLDdi</td>\n",
       "      <td>Order_N7kgLDdi</td>\n",
       "      <td>Trade_DaIBoUOA</td>\n",
       "      <td>future_test</td>\n",
       "      <td>219.5250</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-06-02 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3064.5</td>\n",
       "      <td>-300</td>\n",
       "      <td>1.040801e+06</td>\n",
       "      <td>Order_xW3kadRP</td>\n",
       "      <td>Order_xW3kadRP</td>\n",
       "      <td>Trade_GvHDboia</td>\n",
       "      <td>future_test</td>\n",
       "      <td>229.8375</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-06-16 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3091.0</td>\n",
       "      <td>300</td>\n",
       "      <td>1.132688e+05</td>\n",
       "      <td>Order_To0LnZ6R</td>\n",
       "      <td>Order_To0LnZ6R</td>\n",
       "      <td>Trade_E1KSoZ3M</td>\n",
       "      <td>future_test</td>\n",
       "      <td>231.8250</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-07-21 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3507.0</td>\n",
       "      <td>-300</td>\n",
       "      <td>1.165106e+06</td>\n",
       "      <td>Order_bpRNei6j</td>\n",
       "      <td>Order_bpRNei6j</td>\n",
       "      <td>Trade_pUkThqHy</td>\n",
       "      <td>future_test</td>\n",
       "      <td>263.0250</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-08-02 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3725.0</td>\n",
       "      <td>300</td>\n",
       "      <td>4.732641e+04</td>\n",
       "      <td>Order_B5y7xKVo</td>\n",
       "      <td>Order_B5y7xKVo</td>\n",
       "      <td>Trade_EmQkM2GF</td>\n",
       "      <td>future_test</td>\n",
       "      <td>279.3750</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2017-08-14 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3840.0</td>\n",
       "      <td>-300</td>\n",
       "      <td>1.199038e+06</td>\n",
       "      <td>Order_mXTz7ReE</td>\n",
       "      <td>Order_mXTz7ReE</td>\n",
       "      <td>Trade_fMagl9ej</td>\n",
       "      <td>future_test</td>\n",
       "      <td>288.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2017-10-13 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3815.0</td>\n",
       "      <td>300</td>\n",
       "      <td>5.425229e+04</td>\n",
       "      <td>Order_zd4AiEsW</td>\n",
       "      <td>Order_zd4AiEsW</td>\n",
       "      <td>Trade_6Dw0JClT</td>\n",
       "      <td>future_test</td>\n",
       "      <td>286.1250</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2017-10-27 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3615.0</td>\n",
       "      <td>-300</td>\n",
       "      <td>1.138481e+06</td>\n",
       "      <td>Order_qAVNipPz</td>\n",
       "      <td>Order_qAVNipPz</td>\n",
       "      <td>Trade_9z1H8cDP</td>\n",
       "      <td>future_test</td>\n",
       "      <td>271.1250</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2017-11-06 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3736.0</td>\n",
       "      <td>300</td>\n",
       "      <td>1.740096e+04</td>\n",
       "      <td>Order_4FNMg93m</td>\n",
       "      <td>Order_4FNMg93m</td>\n",
       "      <td>Trade_jxanJK9R</td>\n",
       "      <td>future_test</td>\n",
       "      <td>280.2000</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2017-12-11 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3919.5</td>\n",
       "      <td>-300</td>\n",
       "      <td>1.192957e+06</td>\n",
       "      <td>Order_5pJGeLfD</td>\n",
       "      <td>Order_5pJGeLfD</td>\n",
       "      <td>Trade_1ZR5G0Yu</td>\n",
       "      <td>future_test</td>\n",
       "      <td>293.9625</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2018-01-11 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3838.0</td>\n",
       "      <td>300</td>\n",
       "      <td>4.126915e+04</td>\n",
       "      <td>Order_zsXxkHy6</td>\n",
       "      <td>Order_zsXxkHy6</td>\n",
       "      <td>Trade_NYlTXwvQ</td>\n",
       "      <td>future_test</td>\n",
       "      <td>287.8500</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2018-01-12 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3813.5</td>\n",
       "      <td>-300</td>\n",
       "      <td>1.185033e+06</td>\n",
       "      <td>Order_JH6G4mfx</td>\n",
       "      <td>Order_JH6G4mfx</td>\n",
       "      <td>Trade_a8UICejQ</td>\n",
       "      <td>future_test</td>\n",
       "      <td>286.0125</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2018-01-18 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3859.0</td>\n",
       "      <td>300</td>\n",
       "      <td>2.704371e+04</td>\n",
       "      <td>Order_pqLsA2DI</td>\n",
       "      <td>Order_pqLsA2DI</td>\n",
       "      <td>Trade_0LncPGZ8</td>\n",
       "      <td>future_test</td>\n",
       "      <td>289.4250</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2018-02-08 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3933.5</td>\n",
       "      <td>-300</td>\n",
       "      <td>1.206799e+06</td>\n",
       "      <td>Order_USgTJ8hO</td>\n",
       "      <td>Order_USgTJ8hO</td>\n",
       "      <td>Trade_I27zru8M</td>\n",
       "      <td>future_test</td>\n",
       "      <td>295.0125</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2018-04-10 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3419.0</td>\n",
       "      <td>300</td>\n",
       "      <td>1.808423e+05</td>\n",
       "      <td>Order_sG3do70w</td>\n",
       "      <td>Order_sG3do70w</td>\n",
       "      <td>Trade_RvUZEFp0</td>\n",
       "      <td>future_test</td>\n",
       "      <td>256.4250</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2018-05-21 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3616.5</td>\n",
       "      <td>-300</td>\n",
       "      <td>1.265521e+06</td>\n",
       "      <td>Order_QvmpJ9x8</td>\n",
       "      <td>Order_QvmpJ9x8</td>\n",
       "      <td>Trade_DMbeps1C</td>\n",
       "      <td>future_test</td>\n",
       "      <td>271.2375</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2018-05-31 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3696.0</td>\n",
       "      <td>300</td>\n",
       "      <td>1.564438e+05</td>\n",
       "      <td>Order_dcGMh8tv</td>\n",
       "      <td>Order_dcGMh8tv</td>\n",
       "      <td>Trade_dwLZnTaz</td>\n",
       "      <td>future_test</td>\n",
       "      <td>277.2000</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2018-06-21 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3806.5</td>\n",
       "      <td>-300</td>\n",
       "      <td>1.298108e+06</td>\n",
       "      <td>Order_gb2MiIWy</td>\n",
       "      <td>Order_gb2MiIWy</td>\n",
       "      <td>Trade_DsAMSULd</td>\n",
       "      <td>future_test</td>\n",
       "      <td>285.4875</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2018-07-10 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3862.0</td>\n",
       "      <td>300</td>\n",
       "      <td>1.392187e+05</td>\n",
       "      <td>Order_09bcEx2w</td>\n",
       "      <td>Order_09bcEx2w</td>\n",
       "      <td>Trade_fUpmQPZN</td>\n",
       "      <td>future_test</td>\n",
       "      <td>289.6500</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2018-08-22 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>4360.5</td>\n",
       "      <td>-300</td>\n",
       "      <td>1.447042e+06</td>\n",
       "      <td>Order_cPOyniRg</td>\n",
       "      <td>Order_cPOyniRg</td>\n",
       "      <td>Trade_WXclLstz</td>\n",
       "      <td>future_test</td>\n",
       "      <td>327.0375</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               datetime  code   price  amount          cash        order_id  \\\n",
       "0   2017-04-24 00:00:00  RBL8  2927.0     300  1.216805e+05  Order_N7kgLDdi   \n",
       "1   2017-06-02 00:00:00  RBL8  3064.5    -300  1.040801e+06  Order_xW3kadRP   \n",
       "2   2017-06-16 00:00:00  RBL8  3091.0     300  1.132688e+05  Order_To0LnZ6R   \n",
       "3   2017-07-21 00:00:00  RBL8  3507.0    -300  1.165106e+06  Order_bpRNei6j   \n",
       "4   2017-08-02 00:00:00  RBL8  3725.0     300  4.732641e+04  Order_B5y7xKVo   \n",
       "5   2017-08-14 00:00:00  RBL8  3840.0    -300  1.199038e+06  Order_mXTz7ReE   \n",
       "6   2017-10-13 00:00:00  RBL8  3815.0     300  5.425229e+04  Order_zd4AiEsW   \n",
       "7   2017-10-27 00:00:00  RBL8  3615.0    -300  1.138481e+06  Order_qAVNipPz   \n",
       "8   2017-11-06 00:00:00  RBL8  3736.0     300  1.740096e+04  Order_4FNMg93m   \n",
       "9   2017-12-11 00:00:00  RBL8  3919.5    -300  1.192957e+06  Order_5pJGeLfD   \n",
       "10  2018-01-11 00:00:00  RBL8  3838.0     300  4.126915e+04  Order_zsXxkHy6   \n",
       "11  2018-01-12 00:00:00  RBL8  3813.5    -300  1.185033e+06  Order_JH6G4mfx   \n",
       "12  2018-01-18 00:00:00  RBL8  3859.0     300  2.704371e+04  Order_pqLsA2DI   \n",
       "13  2018-02-08 00:00:00  RBL8  3933.5    -300  1.206799e+06  Order_USgTJ8hO   \n",
       "14  2018-04-10 00:00:00  RBL8  3419.0     300  1.808423e+05  Order_sG3do70w   \n",
       "15  2018-05-21 00:00:00  RBL8  3616.5    -300  1.265521e+06  Order_QvmpJ9x8   \n",
       "16  2018-05-31 00:00:00  RBL8  3696.0     300  1.564438e+05  Order_dcGMh8tv   \n",
       "17  2018-06-21 00:00:00  RBL8  3806.5    -300  1.298108e+06  Order_gb2MiIWy   \n",
       "18  2018-07-10 00:00:00  RBL8  3862.0     300  1.392187e+05  Order_09bcEx2w   \n",
       "19  2018-08-22 00:00:00  RBL8  4360.5    -300  1.447042e+06  Order_cPOyniRg   \n",
       "\n",
       "      realorder_id        trade_id account_cookie  commission  tax message  \n",
       "0   Order_N7kgLDdi  Trade_DaIBoUOA    future_test    219.5250    0    None  \n",
       "1   Order_xW3kadRP  Trade_GvHDboia    future_test    229.8375    0    None  \n",
       "2   Order_To0LnZ6R  Trade_E1KSoZ3M    future_test    231.8250    0    None  \n",
       "3   Order_bpRNei6j  Trade_pUkThqHy    future_test    263.0250    0    None  \n",
       "4   Order_B5y7xKVo  Trade_EmQkM2GF    future_test    279.3750    0    None  \n",
       "5   Order_mXTz7ReE  Trade_fMagl9ej    future_test    288.0000    0    None  \n",
       "6   Order_zd4AiEsW  Trade_6Dw0JClT    future_test    286.1250    0    None  \n",
       "7   Order_qAVNipPz  Trade_9z1H8cDP    future_test    271.1250    0    None  \n",
       "8   Order_4FNMg93m  Trade_jxanJK9R    future_test    280.2000    0    None  \n",
       "9   Order_5pJGeLfD  Trade_1ZR5G0Yu    future_test    293.9625    0    None  \n",
       "10  Order_zsXxkHy6  Trade_NYlTXwvQ    future_test    287.8500    0    None  \n",
       "11  Order_JH6G4mfx  Trade_a8UICejQ    future_test    286.0125    0    None  \n",
       "12  Order_pqLsA2DI  Trade_0LncPGZ8    future_test    289.4250    0    None  \n",
       "13  Order_USgTJ8hO  Trade_I27zru8M    future_test    295.0125    0    None  \n",
       "14  Order_sG3do70w  Trade_RvUZEFp0    future_test    256.4250    0    None  \n",
       "15  Order_QvmpJ9x8  Trade_DMbeps1C    future_test    271.2375    0    None  \n",
       "16  Order_dcGMh8tv  Trade_dwLZnTaz    future_test    277.2000    0    None  \n",
       "17  Order_gb2MiIWy  Trade_DsAMSULd    future_test    285.4875    0    None  \n",
       "18  Order_09bcEx2w  Trade_fUpmQPZN    future_test    289.6500    0    None  \n",
       "19  Order_cPOyniRg  Trade_WXclLstz    future_test    327.0375    0    None  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Account.history_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'RBL8': {2: {'money': 0, 'amount': 0}, -2: {'money': 0, 'amount': 0}}}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Account.frozen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "Risk=QA.QA_Risk(Account,if_fq=False,market_data=rb_ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1000000,\n",
       " 121680.47499999998,\n",
       " 1040800.6375,\n",
       " 113268.8125,\n",
       " 1165105.7875,\n",
       " 47326.41250000009,\n",
       " 1199038.4125,\n",
       " 54252.28750000009,\n",
       " 1138481.1625,\n",
       " 17400.96250000014,\n",
       " 1192957.0000000002,\n",
       " 41269.15000000014,\n",
       " 1185033.1375000002,\n",
       " 27043.71250000014,\n",
       " 1206798.7000000002,\n",
       " 180842.27500000014,\n",
       " 1265521.0375,\n",
       " 156443.83750000014,\n",
       " 1298108.35,\n",
       " 139218.7000000002,\n",
       " 1447041.6625]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Risk.account.cash"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from 'C:\\\\ProgramData\\\\Anaconda3\\\\lib\\\\site-packages\\\\matplotlib\\\\pyplot.py'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x864 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Risk.plot_assets_curve()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'total_buyandsell': 452550.0,\n",
       " 'total_tax': 0.0,\n",
       " 'total_commission': -5508.34,\n",
       " 'total_profit': 447041.66}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Risk.profit_construct"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Risk=QA.QA_Risk(Account)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
